Overview

Dataset statistics

Number of variables21
Number of observations20718
Missing cells2178
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 MiB
Average record size in memory162.0 B

Variable types

Categorical3
Text1
Numeric15
Boolean2

Alerts

Artist has a high cardinality: 2079 distinct valuesHigh cardinality
Album has a high cardinality: 11937 distinct valuesHigh cardinality
Energy is highly overall correlated with Loudness and 1 other fieldsHigh correlation
Loudness is highly overall correlated with EnergyHigh correlation
Acousticness is highly overall correlated with EnergyHigh correlation
Views is highly overall correlated with Likes and 2 other fieldsHigh correlation
Likes is highly overall correlated with Views and 2 other fieldsHigh correlation
Comments is highly overall correlated with Views and 2 other fieldsHigh correlation
Spotify_stream is highly overall correlated with Views and 2 other fieldsHigh correlation
Licensed is highly overall correlated with Official_videoHigh correlation
Official_video is highly overall correlated with LicensedHigh correlation
Views has 470 (2.3%) missing valuesMissing
Likes has 541 (2.6%) missing valuesMissing
Comments has 569 (2.7%) missing valuesMissing
Spotify_stream has 576 (2.8%) missing valuesMissing
Duration_ms is highly skewed (γ1 = 23.37595857)Skewed
Comments is highly skewed (γ1 = 43.69709221)Skewed
Artist is uniformly distributedUniform
Key has 2305 (11.1%) zerosZeros
Instrumentalness has 9391 (45.3%) zerosZeros
Comments has 499 (2.4%) zerosZeros

Reproduction

Analysis started2023-07-16 17:20:42.748686
Analysis finished2023-07-16 17:22:12.935428
Duration1 minute and 30.19 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

Artist
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct2079
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size323.7 KiB
Gorillaz
 
10
Die drei !!!
 
10
Hollywood Undead
 
10
Empire of the Sun
 
10
White Noise for Babies
 
10
Other values (2074)
20668 

Length

Max length45
Median length32
Mean length10.974901
Min length2

Characters and Unicode

Total characters227378
Distinct characters107
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowGorillaz
2nd rowGorillaz
3rd rowGorillaz
4th rowGorillaz
5th rowGorillaz

Common Values

ValueCountFrequency (%)
Gorillaz 10
 
< 0.1%
Die drei !!! 10
 
< 0.1%
Hollywood Undead 10
 
< 0.1%
Empire of the Sun 10
 
< 0.1%
White Noise for Babies 10
 
< 0.1%
IU 10
 
< 0.1%
Kizzy 10
 
< 0.1%
Alan Gomez 10
 
< 0.1%
RÜFÜS DU SOL 10
 
< 0.1%
Bo Burnham 10
 
< 0.1%
Other values (2069) 20618
99.5%

Length

2023-07-16T17:22:13.291594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 840
 
2.1%
439
 
1.1%
los 290
 
0.7%
de 200
 
0.5%
la 150
 
0.4%
el 130
 
0.3%
james 130
 
0.3%
of 130
 
0.3%
john 120
 
0.3%
lil 119
 
0.3%
Other values (2961) 36662
93.5%

Most occurring characters

ValueCountFrequency (%)
a 20453
 
9.0%
e 19243
 
8.5%
18492
 
8.1%
i 13778
 
6.1%
o 13343
 
5.9%
n 12976
 
5.7%
r 12386
 
5.4%
l 9556
 
4.2%
s 9016
 
4.0%
t 7418
 
3.3%
Other values (97) 90717
39.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 162126
71.3%
Uppercase Letter 43822
 
19.3%
Space Separator 18492
 
8.1%
Other Punctuation 1538
 
0.7%
Decimal Number 920
 
0.4%
Dash Punctuation 330
 
0.1%
Currency Symbol 110
 
< 0.1%
Math Symbol 20
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Open Punctuation 10
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 20453
12.6%
e 19243
11.9%
i 13778
 
8.5%
o 13343
 
8.2%
n 12976
 
8.0%
r 12386
 
7.6%
l 9556
 
5.9%
s 9016
 
5.6%
t 7418
 
4.6%
h 6056
 
3.7%
Other values (36) 37901
23.4%
Uppercase Letter
ValueCountFrequency (%)
S 3502
 
8.0%
M 3235
 
7.4%
C 2999
 
6.8%
T 2826
 
6.4%
B 2769
 
6.3%
A 2736
 
6.2%
L 2528
 
5.8%
D 2356
 
5.4%
R 2227
 
5.1%
J 2064
 
4.7%
Other values (24) 16580
37.8%
Other Punctuation
ValueCountFrequency (%)
. 730
47.5%
& 409
26.6%
' 149
 
9.7%
! 70
 
4.6%
" 60
 
3.9%
, 40
 
2.6%
? 30
 
2.0%
/ 20
 
1.3%
* 20
 
1.3%
: 10
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 220
23.9%
2 170
18.5%
5 120
13.0%
4 100
10.9%
0 80
 
8.7%
7 60
 
6.5%
3 50
 
5.4%
6 50
 
5.4%
9 40
 
4.3%
8 30
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 310
93.9%
20
 
6.1%
Space Separator
ValueCountFrequency (%)
18492
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 110
100.0%
Math Symbol
ValueCountFrequency (%)
+ 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 205948
90.6%
Common 21430
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 20453
 
9.9%
e 19243
 
9.3%
i 13778
 
6.7%
o 13343
 
6.5%
n 12976
 
6.3%
r 12386
 
6.0%
l 9556
 
4.6%
s 9016
 
4.4%
t 7418
 
3.6%
h 6056
 
2.9%
Other values (70) 81723
39.7%
Common
ValueCountFrequency (%)
18492
86.3%
. 730
 
3.4%
& 409
 
1.9%
- 310
 
1.4%
1 220
 
1.0%
2 170
 
0.8%
' 149
 
0.7%
5 120
 
0.6%
$ 110
 
0.5%
4 100
 
0.5%
Other values (17) 620
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 225918
99.4%
None 1440
 
0.6%
Punctuation 20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 20453
 
9.1%
e 19243
 
8.5%
18492
 
8.2%
i 13778
 
6.1%
o 13343
 
5.9%
n 12976
 
5.7%
r 12386
 
5.5%
l 9556
 
4.2%
s 9016
 
4.0%
t 7418
 
3.3%
Other values (68) 89257
39.5%
None
ValueCountFrequency (%)
é 320
22.2%
á 190
13.2%
í 190
13.2%
ó 130
9.0%
ü 80
 
5.6%
ã 80
 
5.6%
ö 60
 
4.2%
ñ 60
 
4.2%
ç 50
 
3.5%
è 30
 
2.1%
Other values (18) 250
17.4%
Punctuation
ValueCountFrequency (%)
20
100.0%

Track
Text

Distinct17841
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:14.058872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length195
Median length112
Mean length19.432812
Min length1

Characters and Unicode

Total characters402609
Distinct characters500
Distinct categories18 ?
Distinct scripts9 ?
Distinct blocks13 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15714 ?
Unique (%)75.8%

Sample

1st rowFeel Good Inc.
2nd rowRhinestone Eyes
3rd rowNew Gold (feat. Tame Impala and Bootie Brown)
4th rowOn Melancholy Hill
5th rowClint Eastwood
ValueCountFrequency (%)
3717
 
4.9%
feat 1744
 
2.3%
the 1629
 
2.1%
you 912
 
1.2%
me 903
 
1.2%
a 767
 
1.0%
i 704
 
0.9%
love 646
 
0.8%
of 590
 
0.8%
remix 587
 
0.8%
Other values (15038) 64431
84.1%
2023-07-16T17:22:15.274643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55912
 
13.9%
e 34560
 
8.6%
a 27670
 
6.9%
o 23631
 
5.9%
i 19974
 
5.0%
n 17595
 
4.4%
r 16905
 
4.2%
t 16128
 
4.0%
s 12342
 
3.1%
l 12091
 
3.0%
Other values (490) 165801
41.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 251209
62.4%
Uppercase Letter 71431
 
17.7%
Space Separator 55912
 
13.9%
Other Punctuation 8214
 
2.0%
Decimal Number 5073
 
1.3%
Close Punctuation 3459
 
0.9%
Open Punctuation 3457
 
0.9%
Dash Punctuation 3035
 
0.8%
Other Letter 530
 
0.1%
Final Punctuation 102
 
< 0.1%
Other values (8) 187
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
2.8%
9
 
1.7%
9
 
1.7%
9
 
1.7%
8
 
1.5%
8
 
1.5%
7
 
1.3%
6
 
1.1%
6
 
1.1%
6
 
1.1%
Other values (315) 447
84.3%
Lowercase Letter
ValueCountFrequency (%)
e 34560
13.8%
a 27670
11.0%
o 23631
 
9.4%
i 19974
 
8.0%
n 17595
 
7.0%
r 16905
 
6.7%
t 16128
 
6.4%
s 12342
 
4.9%
l 12091
 
4.8%
u 9010
 
3.6%
Other values (52) 61303
24.4%
Uppercase Letter
ValueCountFrequency (%)
S 5508
 
7.7%
T 5429
 
7.6%
M 5187
 
7.3%
A 5039
 
7.1%
L 4190
 
5.9%
D 3647
 
5.1%
R 3580
 
5.0%
B 3564
 
5.0%
C 3458
 
4.8%
I 3222
 
4.5%
Other values (41) 28607
40.0%
Other Punctuation
ValueCountFrequency (%)
. 2943
35.8%
' 1388
16.9%
, 1146
 
14.0%
" 920
 
11.2%
& 728
 
8.9%
: 414
 
5.0%
/ 237
 
2.9%
? 156
 
1.9%
! 143
 
1.7%
* 41
 
0.5%
Other values (8) 98
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 1183
23.3%
0 1065
21.0%
1 1004
19.8%
5 333
 
6.6%
3 318
 
6.3%
9 281
 
5.5%
4 253
 
5.0%
7 230
 
4.5%
6 217
 
4.3%
8 189
 
3.7%
Math Symbol
ValueCountFrequency (%)
+ 38
54.3%
| 22
31.4%
= 3
 
4.3%
~ 3
 
4.3%
2
 
2.9%
< 1
 
1.4%
1
 
1.4%
Nonspacing Mark
ValueCountFrequency (%)
́ 10
58.8%
̧ 2
 
11.8%
̇ 2
 
11.8%
̃ 1
 
5.9%
1
 
5.9%
1
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 3359
97.1%
] 98
 
2.8%
2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 3357
97.1%
[ 98
 
2.8%
2
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3027
99.7%
7
 
0.2%
1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
4
66.7%
1
 
16.7%
® 1
 
16.7%
Final Punctuation
ValueCountFrequency (%)
89
87.3%
13
 
12.7%
Initial Punctuation
ValueCountFrequency (%)
11
91.7%
1
 
8.3%
Space Separator
ValueCountFrequency (%)
55912
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 60
100.0%
Modifier Letter
ValueCountFrequency (%)
12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 322635
80.1%
Common 79422
 
19.7%
Han 298
 
0.1%
Katakana 114
 
< 0.1%
Hiragana 80
 
< 0.1%
Hangul 33
 
< 0.1%
Inherited 17
 
< 0.1%
Hebrew 5
 
< 0.1%
Greek 5
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
8
 
2.7%
8
 
2.7%
6
 
2.0%
5
 
1.7%
5
 
1.7%
4
 
1.3%
4
 
1.3%
4
 
1.3%
4
 
1.3%
3
 
1.0%
Other values (203) 247
82.9%
Latin
ValueCountFrequency (%)
e 34560
 
10.7%
a 27670
 
8.6%
o 23631
 
7.3%
i 19974
 
6.2%
n 17595
 
5.5%
r 16905
 
5.2%
t 16128
 
5.0%
s 12342
 
3.8%
l 12091
 
3.7%
u 9010
 
2.8%
Other values (98) 132729
41.1%
Common
ValueCountFrequency (%)
55912
70.4%
) 3359
 
4.2%
( 3357
 
4.2%
- 3027
 
3.8%
. 2943
 
3.7%
' 1388
 
1.7%
2 1183
 
1.5%
, 1146
 
1.4%
0 1065
 
1.3%
1 1004
 
1.3%
Other values (46) 5038
 
6.3%
Katakana
ValueCountFrequency (%)
9
 
7.9%
9
 
7.9%
9
 
7.9%
7
 
6.1%
6
 
5.3%
5
 
4.4%
4
 
3.5%
4
 
3.5%
3
 
2.6%
3
 
2.6%
Other values (36) 55
48.2%
Hiragana
ValueCountFrequency (%)
15
18.8%
6
 
7.5%
5
 
6.2%
5
 
6.2%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
2
 
2.5%
2
 
2.5%
Other values (25) 33
41.2%
Hangul
ValueCountFrequency (%)
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (17) 17
51.5%
Inherited
ValueCountFrequency (%)
́ 10
58.8%
̧ 2
 
11.8%
̇ 2
 
11.8%
̃ 1
 
5.9%
1
 
5.9%
1
 
5.9%
Greek
ValueCountFrequency (%)
Ε 1
20.0%
Γ 1
20.0%
Σ 1
20.0%
Δ 1
20.0%
Θ 1
20.0%
Hebrew
ValueCountFrequency (%)
ה 2
40.0%
ש 1
20.0%
ד 1
20.0%
ק 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399547
99.2%
None 2370
 
0.6%
CJK 298
 
0.1%
Katakana 128
 
< 0.1%
Punctuation 124
 
< 0.1%
Hiragana 81
 
< 0.1%
Hangul 33
 
< 0.1%
Diacriticals 15
 
< 0.1%
Hebrew 5
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55912
 
14.0%
e 34560
 
8.6%
a 27670
 
6.9%
o 23631
 
5.9%
i 19974
 
5.0%
n 17595
 
4.4%
r 16905
 
4.2%
t 16128
 
4.0%
s 12342
 
3.1%
l 12091
 
3.0%
Other values (79) 162739
40.7%
None
ValueCountFrequency (%)
é 371
15.7%
ó 319
13.5%
á 269
11.4%
í 259
10.9%
ú 148
 
6.2%
ã 147
 
6.2%
ñ 121
 
5.1%
ç 102
 
4.3%
ü 66
 
2.8%
ı 56
 
2.4%
Other values (58) 512
21.6%
Punctuation
ValueCountFrequency (%)
89
71.8%
13
 
10.5%
11
 
8.9%
7
 
5.6%
2
 
1.6%
1
 
0.8%
1
 
0.8%
Hiragana
ValueCountFrequency (%)
15
18.5%
6
 
7.4%
5
 
6.2%
5
 
6.2%
3
 
3.7%
3
 
3.7%
3
 
3.7%
3
 
3.7%
2
 
2.5%
2
 
2.5%
Other values (26) 34
42.0%
Katakana
ValueCountFrequency (%)
12
 
9.4%
9
 
7.0%
9
 
7.0%
9
 
7.0%
7
 
5.5%
6
 
4.7%
5
 
3.9%
4
 
3.1%
4
 
3.1%
3
 
2.3%
Other values (38) 60
46.9%
Diacriticals
ValueCountFrequency (%)
́ 10
66.7%
̧ 2
 
13.3%
̇ 2
 
13.3%
̃ 1
 
6.7%
CJK
ValueCountFrequency (%)
8
 
2.7%
8
 
2.7%
6
 
2.0%
5
 
1.7%
5
 
1.7%
4
 
1.3%
4
 
1.3%
4
 
1.3%
4
 
1.3%
3
 
1.0%
Other values (203) 247
82.9%
Letterlike Symbols
ValueCountFrequency (%)
4
100.0%
Hebrew
ValueCountFrequency (%)
ה 2
40.0%
ש 1
20.0%
ד 1
20.0%
ק 1
20.0%
Hangul
ValueCountFrequency (%)
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (17) 17
51.5%
Math Operators
ValueCountFrequency (%)
2
100.0%
VS
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%

Album
Categorical

HIGH CARDINALITY 

Distinct11937
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Memory size323.7 KiB
Greatest Hits
 
30
Hamilton (Original Broadway Cast Recording)
 
29
Rebelde
 
25
Madvillainy
 
24
El Ultimo Adiós
 
24
Other values (11932)
20586 

Length

Max length195
Median length103
Mean length20.36046
Min length1

Characters and Unicode

Total characters421828
Distinct characters383
Distinct categories17 ?
Distinct scripts8 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7520 ?
Unique (%)36.3%

Sample

1st rowDemon Days
2nd rowPlastic Beach
3rd rowNew Gold (feat. Tame Impala and Bootie Brown)
4th rowPlastic Beach
5th rowGorillaz

Common Values

ValueCountFrequency (%)
Greatest Hits 30
 
0.1%
Hamilton (Original Broadway Cast Recording) 29
 
0.1%
Rebelde 25
 
0.1%
Madvillainy 24
 
0.1%
El Ultimo Adiós 24
 
0.1%
HEROES & VILLAINS 22
 
0.1%
Nuestro Amor 20
 
0.1%
An Evening With Silk Sonic 20
 
0.1%
Vida Cara 20
 
0.1%
Color Esperanza 2020 19
 
0.1%
Other values (11927) 20485
98.9%

Length

2023-07-16T17:22:15.647947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 2694
 
3.7%
1551
 
2.2%
edition 851
 
1.2%
deluxe 823
 
1.1%
of 817
 
1.1%
original 732
 
1.0%
soundtrack 716
 
1.0%
motion 687
 
1.0%
picture 671
 
0.9%
a 600
 
0.8%
Other values (11896) 61973
85.9%

Most occurring characters

ValueCountFrequency (%)
51397
 
12.2%
e 35131
 
8.3%
a 26138
 
6.2%
o 24756
 
5.9%
i 23909
 
5.7%
n 20632
 
4.9%
r 19241
 
4.6%
t 17484
 
4.1%
s 14327
 
3.4%
l 13808
 
3.3%
Other values (373) 175005
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 270233
64.1%
Uppercase Letter 76726
 
18.2%
Space Separator 51397
 
12.2%
Other Punctuation 6610
 
1.6%
Decimal Number 5452
 
1.3%
Open Punctuation 4875
 
1.2%
Close Punctuation 4875
 
1.2%
Dash Punctuation 933
 
0.2%
Other Letter 377
 
0.1%
Math Symbol 154
 
< 0.1%
Other values (7) 196
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
 
2.7%
10
 
2.7%
10
 
2.7%
9
 
2.4%
7
 
1.9%
6
 
1.6%
6
 
1.6%
5
 
1.3%
4
 
1.1%
4
 
1.1%
Other values (208) 306
81.2%
Lowercase Letter
ValueCountFrequency (%)
e 35131
13.0%
a 26138
9.7%
o 24756
 
9.2%
i 23909
 
8.8%
n 20632
 
7.6%
r 19241
 
7.1%
t 17484
 
6.5%
s 14327
 
5.3%
l 13808
 
5.1%
u 10413
 
3.9%
Other values (48) 64394
23.8%
Uppercase Letter
ValueCountFrequency (%)
S 6472
 
8.4%
T 6089
 
7.9%
A 5486
 
7.2%
M 5121
 
6.7%
E 4996
 
6.5%
D 4314
 
5.6%
L 3879
 
5.1%
R 3695
 
4.8%
C 3665
 
4.8%
O 3628
 
4.7%
Other values (34) 29381
38.3%
Other Punctuation
ValueCountFrequency (%)
. 2036
30.8%
: 930
14.1%
' 897
13.6%
, 768
 
11.6%
& 644
 
9.7%
" 507
 
7.7%
/ 254
 
3.8%
! 215
 
3.3%
? 133
 
2.0%
# 55
 
0.8%
Other values (11) 171
 
2.6%
Decimal Number
ValueCountFrequency (%)
2 1350
24.8%
1 1060
19.4%
0 1027
18.8%
3 476
 
8.7%
5 364
 
6.7%
9 317
 
5.8%
4 281
 
5.2%
7 195
 
3.6%
8 192
 
3.5%
6 190
 
3.5%
Math Symbol
ValueCountFrequency (%)
+ 103
66.9%
| 21
 
13.6%
~ 16
 
10.4%
= 6
 
3.9%
< 3
 
1.9%
÷ 3
 
1.9%
× 1
 
0.6%
1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 4611
94.6%
[ 261
 
5.4%
2
 
< 0.1%
{ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4611
94.6%
] 261
 
5.4%
2
 
< 0.1%
} 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 918
98.4%
14
 
1.5%
1
 
0.1%
Other Symbol
ValueCountFrequency (%)
° 6
50.0%
4
33.3%
® 2
 
16.7%
Final Punctuation
ValueCountFrequency (%)
54
94.7%
3
 
5.3%
Initial Punctuation
ValueCountFrequency (%)
5
62.5%
3
37.5%
Modifier Symbol
ValueCountFrequency (%)
´ 1
50.0%
` 1
50.0%
Space Separator
ValueCountFrequency (%)
51397
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 70
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 28
100.0%
Modifier Letter
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 346956
82.3%
Common 74492
 
17.7%
Han 223
 
0.1%
Katakana 110
 
< 0.1%
Hiragana 32
 
< 0.1%
Greek 5
 
< 0.1%
Hebrew 5
 
< 0.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
10
 
4.5%
4
 
1.8%
4
 
1.8%
4
 
1.8%
4
 
1.8%
3
 
1.3%
3
 
1.3%
3
 
1.3%
3
 
1.3%
3
 
1.3%
Other values (142) 182
81.6%
Latin
ValueCountFrequency (%)
e 35131
 
10.1%
a 26138
 
7.5%
o 24756
 
7.1%
i 23909
 
6.9%
n 20632
 
5.9%
r 19241
 
5.5%
t 17484
 
5.0%
s 14327
 
4.1%
l 13808
 
4.0%
u 10413
 
3.0%
Other values (92) 141117
40.7%
Common
ValueCountFrequency (%)
51397
69.0%
( 4611
 
6.2%
) 4611
 
6.2%
. 2036
 
2.7%
2 1350
 
1.8%
1 1060
 
1.4%
0 1027
 
1.4%
: 930
 
1.2%
- 918
 
1.2%
' 897
 
1.2%
Other values (53) 5655
 
7.6%
Katakana
ValueCountFrequency (%)
10
 
9.1%
10
 
9.1%
9
 
8.2%
7
 
6.4%
6
 
5.5%
6
 
5.5%
4
 
3.6%
4
 
3.6%
4
 
3.6%
4
 
3.6%
Other values (25) 46
41.8%
Hiragana
ValueCountFrequency (%)
5
15.6%
3
 
9.4%
3
 
9.4%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (11) 11
34.4%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Hebrew
ValueCountFrequency (%)
ה 2
40.0%
ק 1
20.0%
ד 1
20.0%
ש 1
20.0%
Greek
ValueCountFrequency (%)
Ξ 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419276
99.4%
None 2066
 
0.5%
CJK 223
 
0.1%
Katakana 129
 
< 0.1%
Punctuation 87
 
< 0.1%
Hiragana 32
 
< 0.1%
Hebrew 5
 
< 0.1%
Hangul 5
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51397
 
12.3%
e 35131
 
8.4%
a 26138
 
6.2%
o 24756
 
5.9%
i 23909
 
5.7%
n 20632
 
4.9%
r 19241
 
4.6%
t 17484
 
4.2%
s 14327
 
3.4%
l 13808
 
3.3%
Other values (83) 172453
41.1%
None
ValueCountFrequency (%)
ó 305
14.8%
é 296
14.3%
í 194
 
9.4%
á 178
 
8.6%
ú 128
 
6.2%
ñ 124
 
6.0%
ü 120
 
5.8%
ã 105
 
5.1%
ç 74
 
3.6%
ı 54
 
2.6%
Other values (53) 488
23.6%
Punctuation
ValueCountFrequency (%)
54
62.1%
14
 
16.1%
7
 
8.0%
5
 
5.7%
3
 
3.4%
3
 
3.4%
1
 
1.1%
Katakana
ValueCountFrequency (%)
19
 
14.7%
10
 
7.8%
10
 
7.8%
9
 
7.0%
7
 
5.4%
6
 
4.7%
6
 
4.7%
4
 
3.1%
4
 
3.1%
4
 
3.1%
Other values (26) 50
38.8%
CJK
ValueCountFrequency (%)
10
 
4.5%
4
 
1.8%
4
 
1.8%
4
 
1.8%
4
 
1.8%
3
 
1.3%
3
 
1.3%
3
 
1.3%
3
 
1.3%
3
 
1.3%
Other values (142) 182
81.6%
Hiragana
ValueCountFrequency (%)
5
15.6%
3
 
9.4%
3
 
9.4%
3
 
9.4%
2
 
6.2%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
1
 
3.1%
Other values (11) 11
34.4%
Letterlike Symbols
ValueCountFrequency (%)
4
100.0%
Hebrew
ValueCountFrequency (%)
ה 2
40.0%
ק 1
20.0%
ד 1
20.0%
ש 1
20.0%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

Album_type
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size323.7 KiB
album
14926 
single
5004 
compilation
 
788

Length

Max length11
Median length5
Mean length5.4697365
Min length5

Characters and Unicode

Total characters113322
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowalbum
2nd rowalbum
3rd rowsingle
4th rowalbum
5th rowalbum

Common Values

ValueCountFrequency (%)
album 14926
72.0%
single 5004
 
24.2%
compilation 788
 
3.8%

Length

2023-07-16T17:22:15.969930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-16T17:22:16.205899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
album 14926
72.0%
single 5004
 
24.2%
compilation 788
 
3.8%

Most occurring characters

ValueCountFrequency (%)
l 20718
18.3%
a 15714
13.9%
m 15714
13.9%
b 14926
13.2%
u 14926
13.2%
i 6580
 
5.8%
n 5792
 
5.1%
s 5004
 
4.4%
g 5004
 
4.4%
e 5004
 
4.4%
Other values (4) 3940
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 113322
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 20718
18.3%
a 15714
13.9%
m 15714
13.9%
b 14926
13.2%
u 14926
13.2%
i 6580
 
5.8%
n 5792
 
5.1%
s 5004
 
4.4%
g 5004
 
4.4%
e 5004
 
4.4%
Other values (4) 3940
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 113322
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 20718
18.3%
a 15714
13.9%
m 15714
13.9%
b 14926
13.2%
u 14926
13.2%
i 6580
 
5.8%
n 5792
 
5.1%
s 5004
 
4.4%
g 5004
 
4.4%
e 5004
 
4.4%
Other values (4) 3940
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 20718
18.3%
a 15714
13.9%
m 15714
13.9%
b 14926
13.2%
u 14926
13.2%
i 6580
 
5.8%
n 5792
 
5.1%
s 5004
 
4.4%
g 5004
 
4.4%
e 5004
 
4.4%
Other values (4) 3940
 
3.5%

Danceability
Real number (ℝ)

Distinct898
Distinct (%)4.3%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.61977745
Minimum0
Maximum0.975
Zeros17
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:16.493767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.319
Q10.518
median0.637
Q30.74025
95-th percentile0.861
Maximum0.975
Range0.975
Interquartile range (IQR)0.22225

Descriptive statistics

Standard deviation0.16527239
Coefficient of variation (CV)0.26666409
Kurtosis0.13707564
Mean0.61977745
Median Absolute Deviation (MAD)0.11
Skewness-0.55015414
Sum12839.31
Variance0.027314963
MonotonicityNot monotonic
2023-07-16T17:22:17.046039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.687 78
 
0.4%
0.671 74
 
0.4%
0.626 69
 
0.3%
0.647 68
 
0.3%
0.682 67
 
0.3%
0.585 66
 
0.3%
0.673 64
 
0.3%
0.681 64
 
0.3%
0.638 63
 
0.3%
0.646 62
 
0.3%
Other values (888) 20041
96.7%
ValueCountFrequency (%)
0 17
0.1%
0.0532 1
 
< 0.1%
0.0619 1
 
< 0.1%
0.0623 1
 
< 0.1%
0.064 1
 
< 0.1%
0.0649 1
 
< 0.1%
0.065 1
 
< 0.1%
0.0673 1
 
< 0.1%
0.0686 1
 
< 0.1%
0.069 1
 
< 0.1%
ValueCountFrequency (%)
0.975 3
< 0.1%
0.973 1
 
< 0.1%
0.971 2
< 0.1%
0.97 4
< 0.1%
0.969 1
 
< 0.1%
0.968 1
 
< 0.1%
0.967 3
< 0.1%
0.966 1
 
< 0.1%
0.965 2
< 0.1%
0.964 4
< 0.1%

Energy
Real number (ℝ)

HIGH CORRELATION 

Distinct1268
Distinct (%)6.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.63525035
Minimum2.03 × 10-5
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:17.580675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.03 × 10-5
5-th percentile0.22
Q10.507
median0.666
Q30.798
95-th percentile0.929
Maximum1
Range0.9999797
Interquartile range (IQR)0.291

Descriptive statistics

Standard deviation0.21414683
Coefficient of variation (CV)0.3371062
Kurtosis0.13887264
Mean0.63525035
Median Absolute Deviation (MAD)0.143
Skewness-0.71485192
Sum13159.846
Variance0.045858865
MonotonicityNot monotonic
2023-07-16T17:22:18.139575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.572 60
 
0.3%
0.711 57
 
0.3%
0.72 57
 
0.3%
0.785 56
 
0.3%
0.768 56
 
0.3%
0.674 55
 
0.3%
0.703 54
 
0.3%
0.782 54
 
0.3%
0.745 53
 
0.3%
0.723 53
 
0.3%
Other values (1258) 20161
97.3%
ValueCountFrequency (%)
2.03 × 10-51
 
< 0.1%
5.5 × 10-52
< 0.1%
0.000252 2
< 0.1%
0.00125 3
< 0.1%
0.00144 1
 
< 0.1%
0.00174 1
 
< 0.1%
0.00189 1
 
< 0.1%
0.00194 1
 
< 0.1%
0.00199 1
 
< 0.1%
0.00212 1
 
< 0.1%
ValueCountFrequency (%)
1 6
< 0.1%
0.999 1
 
< 0.1%
0.998 5
< 0.1%
0.997 3
 
< 0.1%
0.996 7
< 0.1%
0.995 10
< 0.1%
0.994 10
< 0.1%
0.993 5
< 0.1%
0.992 5
< 0.1%
0.991 8
< 0.1%

Key
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.3003476
Minimum0
Maximum11
Zeros2305
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:18.594821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5764485
Coefficient of variation (CV)0.67475736
Kurtosis-1.2980009
Mean5.3003476
Median Absolute Deviation (MAD)3
Skewness-0.0045108915
Sum109802
Variance12.790984
MonotonicityNot monotonic
2023-07-16T17:22:19.043945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 2305
11.1%
7 2252
10.9%
1 2211
10.7%
2 2021
9.8%
9 1979
9.6%
5 1731
8.4%
11 1667
8.0%
4 1515
7.3%
8 1483
7.2%
6 1443
7.0%
Other values (2) 2109
10.2%
ValueCountFrequency (%)
0 2305
11.1%
1 2211
10.7%
2 2021
9.8%
3 670
 
3.2%
4 1515
7.3%
5 1731
8.4%
6 1443
7.0%
7 2252
10.9%
8 1483
7.2%
9 1979
9.6%
ValueCountFrequency (%)
11 1667
8.0%
10 1439
6.9%
9 1979
9.6%
8 1483
7.2%
7 2252
10.9%
6 1443
7.0%
5 1731
8.4%
4 1515
7.3%
3 670
 
3.2%
2 2021
9.8%

Loudness
Real number (ℝ)

HIGH CORRELATION 

Distinct9417
Distinct (%)45.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-7.6716803
Minimum-46.251
Maximum0.92
Zeros0
Zeros (%)0.0%
Negative20710
Negative (%)> 99.9%
Memory size323.7 KiB
2023-07-16T17:22:19.517902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-46.251
5-th percentile-15.8895
Q1-8.858
median-6.536
Q3-4.931
95-th percentile-3.199
Maximum0.92
Range47.171
Interquartile range (IQR)3.927

Descriptive statistics

Standard deviation4.6327486
Coefficient of variation (CV)-0.60387664
Kurtosis10.735181
Mean-7.6716803
Median Absolute Deviation (MAD)1.835
Skewness-2.700817
Sum-158926.53
Variance21.462359
MonotonicityNot monotonic
2023-07-16T17:22:20.062543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.818 25
 
0.1%
-7.768 21
 
0.1%
-4.501 16
 
0.1%
-6.887 15
 
0.1%
-6.253 14
 
0.1%
-6.246 12
 
0.1%
-5.76 12
 
0.1%
-5.077 12
 
0.1%
-5.549 11
 
0.1%
-4.592 11
 
0.1%
Other values (9407) 20567
99.3%
ValueCountFrequency (%)
-46.251 1
< 0.1%
-44.761 1
< 0.1%
-43.988 1
< 0.1%
-41.932 1
< 0.1%
-41.766 1
< 0.1%
-41.696 1
< 0.1%
-41.53 2
< 0.1%
-41.001 1
< 0.1%
-39.919 1
< 0.1%
-39.869 1
< 0.1%
ValueCountFrequency (%)
0.92 1
 
< 0.1%
0.829 1
 
< 0.1%
0.561 1
 
< 0.1%
0.522 1
 
< 0.1%
0.175 1
 
< 0.1%
0.006 1
 
< 0.1%
-0.007 1
 
< 0.1%
-0.14 1
 
< 0.1%
-0.142 1
 
< 0.1%
-0.155 4
< 0.1%

Speechiness
Real number (ℝ)

Distinct1303
Distinct (%)6.3%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.096456005
Minimum0
Maximum0.964
Zeros17
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:20.598293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0278
Q10.0357
median0.0505
Q30.103
95-th percentile0.324
Maximum0.964
Range0.964
Interquartile range (IQR)0.0673

Descriptive statistics

Standard deviation0.11196003
Coefficient of variation (CV)1.1607367
Kurtosis16.499958
Mean0.096456005
Median Absolute Deviation (MAD)0.0192
Skewness3.3736906
Sum1998.1826
Variance0.012535048
MonotonicityNot monotonic
2023-07-16T17:22:21.158913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0324 72
 
0.3%
0.0305 68
 
0.3%
0.0288 65
 
0.3%
0.0317 65
 
0.3%
0.0293 64
 
0.3%
0.0326 64
 
0.3%
0.0315 63
 
0.3%
0.0377 63
 
0.3%
0.0308 62
 
0.3%
0.0306 62
 
0.3%
Other values (1293) 20068
96.9%
ValueCountFrequency (%)
0 17
0.1%
0.022 1
 
< 0.1%
0.0222 1
 
< 0.1%
0.0224 1
 
< 0.1%
0.0225 1
 
< 0.1%
0.0226 1
 
< 0.1%
0.0227 1
 
< 0.1%
0.0229 1
 
< 0.1%
0.023 2
 
< 0.1%
0.0231 1
 
< 0.1%
ValueCountFrequency (%)
0.964 1
< 0.1%
0.962 1
< 0.1%
0.961 2
< 0.1%
0.96 2
< 0.1%
0.959 2
< 0.1%
0.956 1
< 0.1%
0.955 1
< 0.1%
0.954 1
< 0.1%
0.953 1
< 0.1%
0.952 1
< 0.1%

Acousticness
Real number (ℝ)

HIGH CORRELATION 

Distinct3138
Distinct (%)15.1%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.29153535
Minimum1.11 × 10-6
Maximum0.996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:21.696100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11 × 10-6
5-th percentile0.00162
Q10.0452
median0.193
Q30.47725
95-th percentile0.885
Maximum0.996
Range0.99599889
Interquartile range (IQR)0.43205

Descriptive statistics

Standard deviation0.28629882
Coefficient of variation (CV)0.98203808
Kurtosis-0.38256817
Mean0.29153535
Median Absolute Deviation (MAD)0.174
Skewness0.88309151
Sum6039.4463
Variance0.081967012
MonotonicityNot monotonic
2023-07-16T17:22:22.166431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.114 50
 
0.2%
0.161 49
 
0.2%
0.117 45
 
0.2%
0.105 44
 
0.2%
0.118 41
 
0.2%
0.181 40
 
0.2%
0.121 40
 
0.2%
0.173 39
 
0.2%
0.191 37
 
0.2%
0.134 36
 
0.2%
Other values (3128) 20295
98.0%
ValueCountFrequency (%)
1.11 × 10-61
< 0.1%
1.39 × 10-61
< 0.1%
1.77 × 10-61
< 0.1%
2.33 × 10-61
< 0.1%
2.6 × 10-61
< 0.1%
3.19 × 10-61
< 0.1%
3.88 × 10-61
< 0.1%
4 × 10-61
< 0.1%
4.2 × 10-61
< 0.1%
4.21 × 10-61
< 0.1%
ValueCountFrequency (%)
0.996 19
0.1%
0.995 27
0.1%
0.994 27
0.1%
0.993 21
0.1%
0.992 20
0.1%
0.991 18
0.1%
0.99 13
0.1%
0.989 17
0.1%
0.988 16
0.1%
0.987 16
0.1%

Instrumentalness
Real number (ℝ)

ZEROS 

Distinct4012
Distinct (%)19.4%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.055961558
Minimum0
Maximum1
Zeros9391
Zeros (%)45.3%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:22.477206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.405 × 10-6
Q30.000463
95-th percentile0.58
Maximum1
Range1
Interquartile range (IQR)0.000463

Descriptive statistics

Standard deviation0.19326203
Coefficient of variation (CV)3.4534784
Kurtosis12.664126
Mean0.055961558
Median Absolute Deviation (MAD)2.405 × 10-6
Skewness3.720041
Sum1159.2996
Variance0.037350213
MonotonicityNot monotonic
2023-07-16T17:22:22.802036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9391
45.3%
1.4 × 10-517
 
0.1%
0.00106 16
 
0.1%
1.34 × 10-616
 
0.1%
0.109 15
 
0.1%
1.31 × 10-615
 
0.1%
1.1 × 10-615
 
0.1%
1.16 × 10-515
 
0.1%
1.2 × 10-515
 
0.1%
1.28 × 10-515
 
0.1%
Other values (4002) 11186
54.0%
ValueCountFrequency (%)
0 9391
45.3%
1 × 10-69
 
< 0.1%
1.01 × 10-65
 
< 0.1%
1.02 × 10-615
 
0.1%
1.03 × 10-610
 
< 0.1%
1.04 × 10-613
 
0.1%
1.05 × 10-68
 
< 0.1%
1.06 × 10-69
 
< 0.1%
1.07 × 10-610
 
< 0.1%
1.08 × 10-68
 
< 0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.999 1
 
< 0.1%
0.995 3
 
< 0.1%
0.993 1
 
< 0.1%
0.992 2
 
< 0.1%
0.989 2
 
< 0.1%
0.988 4
< 0.1%
0.986 2
 
< 0.1%
0.985 1
 
< 0.1%
0.983 1
 
< 0.1%

Liveness
Real number (ℝ)

Distinct1536
Distinct (%)7.4%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.193521
Minimum0.0145
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:23.120652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0145
5-th percentile0.058375
Q10.0941
median0.125
Q30.237
95-th percentile0.573
Maximum1
Range0.9855
Interquartile range (IQR)0.1429

Descriptive statistics

Standard deviation0.1685309
Coefficient of variation (CV)0.87086623
Kurtosis5.8521745
Mean0.193521
Median Absolute Deviation (MAD)0.0453
Skewness2.310133
Sum4008.981
Variance0.028402665
MonotonicityNot monotonic
2023-07-16T17:22:23.449934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 237
 
1.1%
0.109 226
 
1.1%
0.111 215
 
1.0%
0.107 215
 
1.0%
0.108 211
 
1.0%
0.104 201
 
1.0%
0.103 195
 
0.9%
0.105 185
 
0.9%
0.101 185
 
0.9%
0.112 175
 
0.8%
Other values (1526) 18671
90.1%
ValueCountFrequency (%)
0.0145 1
< 0.1%
0.015 1
< 0.1%
0.0157 1
< 0.1%
0.0158 1
< 0.1%
0.0181 1
< 0.1%
0.0182 1
< 0.1%
0.0188 1
< 0.1%
0.019 2
< 0.1%
0.0199 1
< 0.1%
0.02 1
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0.997 1
 
< 0.1%
0.99 1
 
< 0.1%
0.986 1
 
< 0.1%
0.984 7
< 0.1%
0.983 5
< 0.1%
0.982 2
 
< 0.1%
0.98 2
 
< 0.1%
0.978 2
 
< 0.1%
0.977 5
< 0.1%

Valence
Real number (ℝ)

Distinct1293
Distinct (%)6.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.52985332
Minimum0
Maximum0.993
Zeros26
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:23.769885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.119
Q10.339
median0.537
Q30.72625
95-th percentile0.921
Maximum0.993
Range0.993
Interquartile range (IQR)0.38725

Descriptive statistics

Standard deviation0.24544081
Coefficient of variation (CV)0.46322406
Kurtosis-0.92958849
Mean0.52985332
Median Absolute Deviation (MAD)0.194
Skewness-0.10078553
Sum10976.441
Variance0.060241191
MonotonicityNot monotonic
2023-07-16T17:22:24.095211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.961 71
 
0.3%
0.785 51
 
0.2%
0.962 47
 
0.2%
0.637 44
 
0.2%
0.491 44
 
0.2%
0.595 44
 
0.2%
0.964 43
 
0.2%
0.285 43
 
0.2%
0.284 42
 
0.2%
0.353 41
 
0.2%
Other values (1283) 20246
97.7%
ValueCountFrequency (%)
0 26
0.1%
1 × 10-521
0.1%
0.00237 1
 
< 0.1%
0.00294 1
 
< 0.1%
0.00987 2
 
< 0.1%
0.0129 1
 
< 0.1%
0.0144 1
 
< 0.1%
0.0153 1
 
< 0.1%
0.0154 2
 
< 0.1%
0.0185 3
 
< 0.1%
ValueCountFrequency (%)
0.993 1
 
< 0.1%
0.991 1
 
< 0.1%
0.99 1
 
< 0.1%
0.989 1
 
< 0.1%
0.986 1
 
< 0.1%
0.985 2
< 0.1%
0.984 2
< 0.1%
0.982 2
< 0.1%
0.981 2
< 0.1%
0.98 4
< 0.1%

Tempo
Real number (ℝ)

Distinct15024
Distinct (%)72.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean120.63834
Minimum0
Maximum243.372
Zeros17
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:24.404187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile78.4305
Q197.002
median119.965
Q3139.935
95-th percentile174.794
Maximum243.372
Range243.372
Interquartile range (IQR)42.933

Descriptive statistics

Standard deviation29.579018
Coefficient of variation (CV)0.24518754
Kurtosis-0.13017291
Mean120.63834
Median Absolute Deviation (MAD)21.2055
Skewness0.3931929
Sum2499143.9
Variance874.91828
MonotonicityNot monotonic
2023-07-16T17:22:24.728517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77.986 24
 
0.1%
106.002 19
 
0.1%
0 17
 
0.1%
120.031 12
 
0.1%
119.982 11
 
0.1%
129.971 10
 
< 0.1%
120.057 10
 
< 0.1%
100.015 10
 
< 0.1%
140.006 10
 
< 0.1%
106.001 9
 
< 0.1%
Other values (15014) 20584
99.4%
ValueCountFrequency (%)
0 17
0.1%
37.114 1
 
< 0.1%
38.137 1
 
< 0.1%
43.509 1
 
< 0.1%
45.397 1
 
< 0.1%
46.718 1
 
< 0.1%
47.362 3
 
< 0.1%
48.028 1
 
< 0.1%
48.19 2
 
< 0.1%
48.637 1
 
< 0.1%
ValueCountFrequency (%)
243.372 1
< 0.1%
236.059 1
< 0.1%
220.099 1
< 0.1%
215.918 1
< 0.1%
214.025 1
< 0.1%
213.503 1
< 0.1%
211.958 1
< 0.1%
210.857 1
< 0.1%
209.953 1
< 0.1%
209.795 1
< 0.1%

Duration_ms
Real number (ℝ)

SKEWED 

Distinct14690
Distinct (%)70.9%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean224717.58
Minimum30985
Maximum4676058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:25.193418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30985
5-th percentile133707.75
Q1180009.5
median213284.5
Q3252443
95-th percentile335837
Maximum4676058
Range4645073
Interquartile range (IQR)72433.5

Descriptive statistics

Standard deviation124790.54
Coefficient of variation (CV)0.55532168
Kurtosis788.22417
Mean224717.58
Median Absolute Deviation (MAD)35751.5
Skewness23.375959
Sum4.6552494 × 109
Variance1.557268 × 1010
MonotonicityNot monotonic
2023-07-16T17:22:25.651513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
237467 26
 
0.1%
217547 19
 
0.1%
216000 18
 
0.1%
180000 12
 
0.1%
240000 12
 
0.1%
160000 12
 
0.1%
170000 10
 
< 0.1%
31000 10
 
< 0.1%
192000 10
 
< 0.1%
252443 9
 
< 0.1%
Other values (14680) 20578
99.3%
ValueCountFrequency (%)
30985 1
 
< 0.1%
31000 10
< 0.1%
31437 1
 
< 0.1%
35000 1
 
< 0.1%
37000 1
 
< 0.1%
38000 2
 
< 0.1%
39000 2
 
< 0.1%
40000 1
 
< 0.1%
41000 1
 
< 0.1%
42000 1
 
< 0.1%
ValueCountFrequency (%)
4676058 1
 
< 0.1%
4581483 9
< 0.1%
4120258 1
 
< 0.1%
3340672 1
 
< 0.1%
1484260 1
 
< 0.1%
1427979 1
 
< 0.1%
1330157 2
 
< 0.1%
983432 1
 
< 0.1%
975267 1
 
< 0.1%
944325 1
 
< 0.1%

Views
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19245
Distinct (%)95.0%
Missing470
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean93937821
Minimum0
Maximum8.0796494 × 109
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:25.968539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46764.8
Q11826001.5
median14501095
Q370399749
95-th percentile4.3342305 × 108
Maximum8.0796494 × 109
Range8.0796494 × 109
Interquartile range (IQR)68573748

Descriptive statistics

Standard deviation2.7464432 × 108
Coefficient of variation (CV)2.9236821
Kurtosis148.79317
Mean93937821
Median Absolute Deviation (MAD)14269355
Skewness9.2378329
Sum1.902053 × 1012
Variance7.5429504 × 1016
MonotonicityNot monotonic
2023-07-16T17:22:26.304548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98701312 10
 
< 0.1%
1012205556 10
 
< 0.1%
3877674 10
 
< 0.1%
99348431 10
 
< 0.1%
76238633 10
 
< 0.1%
433396 10
 
< 0.1%
8266725 10
 
< 0.1%
641407658 10
 
< 0.1%
6639 10
 
< 0.1%
3020790 10
 
< 0.1%
Other values (19235) 20148
97.2%
(Missing) 470
 
2.3%
ValueCountFrequency (%)
0 1
< 0.1%
2 1
< 0.1%
7 1
< 0.1%
8 2
< 0.1%
15 1
< 0.1%
21 2
< 0.1%
24 1
< 0.1%
26 1
< 0.1%
28 1
< 0.1%
31 1
< 0.1%
ValueCountFrequency (%)
8079649362 1
< 0.1%
8079646911 1
< 0.1%
5908398479 1
< 0.1%
5773798407 1
< 0.1%
5773797147 1
< 0.1%
4898831101 1
< 0.1%
4821016218 1
< 0.1%
4679767471 1
< 0.1%
3817733132 1
< 0.1%
3725748519 1
< 0.1%

Likes
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17939
Distinct (%)88.9%
Missing541
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean663341.06
Minimum0
Maximum50788652
Zeros18
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:26.634637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile700.4
Q121581
median124481
Q3522148
95-th percentile3007155
Maximum50788652
Range50788652
Interquartile range (IQR)500567

Descriptive statistics

Standard deviation1789324.2
Coefficient of variation (CV)2.6974423
Kurtosis135.47186
Mean663341.06
Median Absolute Deviation (MAD)120607
Skewness8.6707821
Sum1.3384233 × 1010
Variance3.2016813 × 1012
MonotonicityNot monotonic
2023-07-16T17:22:26.957146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
0.1%
5730 14
 
0.1%
32 13
 
0.1%
12 13
 
0.1%
1 12
 
0.1%
256 12
 
0.1%
21 11
 
0.1%
4923 10
 
< 0.1%
449797 10
 
< 0.1%
143480 10
 
< 0.1%
Other values (17929) 20054
96.8%
(Missing) 541
 
2.6%
ValueCountFrequency (%)
0 18
0.1%
1 12
0.1%
2 6
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 3
 
< 0.1%
8 2
 
< 0.1%
9 6
 
< 0.1%
ValueCountFrequency (%)
50788652 1
< 0.1%
50788626 1
< 0.1%
40147674 1
< 0.1%
40147618 1
< 0.1%
35892575 1
< 0.1%
31047780 1
< 0.1%
27588224 1
< 0.1%
27588189 1
< 0.1%
26446178 1
< 0.1%
26399133 1
< 0.1%

Comments
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct10485
Distinct (%)52.0%
Missing569
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean27518.994
Minimum0
Maximum16083138
Zeros499
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:27.256357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q1509
median3277
Q314360
95-th percentile101037.6
Maximum16083138
Range16083138
Interquartile range (IQR)13851

Descriptive statistics

Standard deviation193234.69
Coefficient of variation (CV)7.0218661
Kurtosis2862.4274
Mean27518.994
Median Absolute Deviation (MAD)3202
Skewness43.697092
Sum5.544802 × 108
Variance3.7339645 × 1010
MonotonicityNot monotonic
2023-07-16T17:22:27.588357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 499
 
2.4%
2 85
 
0.4%
1 85
 
0.4%
4 63
 
0.3%
7 58
 
0.3%
6 54
 
0.3%
3 51
 
0.2%
5 49
 
0.2%
21 46
 
0.2%
12 41
 
0.2%
Other values (10475) 19118
92.3%
(Missing) 569
 
2.7%
ValueCountFrequency (%)
0 499
2.4%
1 85
 
0.4%
2 85
 
0.4%
3 51
 
0.2%
4 63
 
0.3%
5 49
 
0.2%
6 54
 
0.3%
7 58
 
0.3%
8 37
 
0.2%
9 34
 
0.2%
ValueCountFrequency (%)
16083138 1
< 0.1%
9131761 1
< 0.1%
6535721 1
< 0.1%
6535719 1
< 0.1%
5331537 1
< 0.1%
5130725 1
< 0.1%
4805805 1
< 0.1%
4252791 2
< 0.1%
3637659 1
< 0.1%
3486944 1
< 0.1%

Licensed
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size182.1 KiB
True
14610 
False
6108 
ValueCountFrequency (%)
True 14610
70.5%
False 6108
29.5%
2023-07-16T17:22:27.860086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Official_video
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size182.1 KiB
True
16193 
False
4525 
ValueCountFrequency (%)
True 16193
78.2%
False 4525
 
21.8%
2023-07-16T17:22:28.076183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Spotify_stream
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18461
Distinct (%)91.7%
Missing576
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean1.3594219 × 108
Minimum6574
Maximum3.3865203 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size323.7 KiB
2023-07-16T17:22:28.332626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6574
5-th percentile2635165
Q117674864
median49682982
Q31.3835807 × 108
95-th percentile5.7812177 × 108
Maximum3.3865203 × 109
Range3.3865137 × 109
Interquartile range (IQR)1.206832 × 108

Descriptive statistics

Standard deviation2.4413208 × 108
Coefficient of variation (CV)1.7958522
Kurtosis23.156929
Mean1.3594219 × 108
Median Absolute Deviation (MAD)39988332
Skewness4.1126427
Sum2.7381476 × 1012
Variance5.9600471 × 1016
MonotonicityNot monotonic
2023-07-16T17:22:28.664688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
169769959 24
 
0.1%
89466323 19
 
0.1%
179230151 9
 
< 0.1%
23128326 9
 
< 0.1%
9999321 9
 
< 0.1%
55399812 9
 
< 0.1%
48533462 9
 
< 0.1%
61921081 7
 
< 0.1%
71682526 7
 
< 0.1%
44902959 6
 
< 0.1%
Other values (18451) 20034
96.7%
(Missing) 576
 
2.8%
ValueCountFrequency (%)
6574 1
< 0.1%
7771 1
< 0.1%
8053 1
< 0.1%
8074 1
< 0.1%
10306 1
< 0.1%
10540 1
< 0.1%
10660 1
< 0.1%
10701 1
< 0.1%
10710 1
< 0.1%
10798 1
< 0.1%
ValueCountFrequency (%)
3386520288 1
< 0.1%
3362005201 1
< 0.1%
2634013335 1
< 0.1%
2594926619 1
< 0.1%
2538329799 2
< 0.1%
2522431995 1
< 0.1%
2456205158 2
< 0.1%
2369272335 1
< 0.1%
2365777505 2
< 0.1%
2336219850 2
< 0.1%

Interactions

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2023-07-16T17:21:59.180040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:22:04.320932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:22:10.416475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:20:59.021742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:03.799685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:08.726974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:14.094477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:18.989220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:23.723615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:28.598893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:33.610664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:39.329340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:44.368463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:49.357303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:54.539977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:59.513728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:22:04.663670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:22:10.656255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:20:59.348261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:04.161205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:09.081048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:14.437314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:19.307743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:24.088647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:28.923800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:33.993903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:39.683667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:44.728234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:49.719913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:54.902250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:21:59.873129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-16T17:22:05.035611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-07-16T17:22:28.931948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
DanceabilityEnergyKeyLoudnessSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoDuration_msViewsLikesCommentsSpotify_streamAlbum_typeLicensedOfficial_video
Danceability1.0000.1210.0360.1960.314-0.140-0.147-0.1080.433-0.070-0.1410.1330.1560.1150.0520.1160.0190.052
Energy0.1211.0000.0270.7100.236-0.572-0.0740.1420.3470.1440.0180.1390.1280.1530.0450.0750.0850.115
Key0.0360.0271.0000.0230.032-0.0260.000-0.0150.0410.000-0.0050.0130.0160.012-0.0070.0430.0000.008
Loudness0.1960.7100.0231.0000.184-0.436-0.2930.0830.2420.117-0.0440.2510.2570.2540.1410.1090.1100.154
Speechiness0.3140.2360.0320.1841.000-0.147-0.1940.0510.1300.070-0.1610.0260.0860.065-0.0180.0700.0640.068
Acousticness-0.140-0.572-0.026-0.436-0.1471.0000.000-0.043-0.108-0.136-0.061-0.119-0.127-0.166-0.1150.0510.0710.091
Instrumentalness-0.147-0.0740.000-0.293-0.1940.0001.000-0.087-0.160-0.0220.062-0.182-0.183-0.163-0.1130.0330.0580.066
Liveness-0.1080.142-0.0150.0830.051-0.043-0.0871.000-0.0170.007-0.020-0.012-0.017-0.007-0.0320.0290.0130.008
Valence0.4330.3470.0410.2420.130-0.108-0.160-0.0171.0000.072-0.0940.0800.0380.025-0.0060.0470.0390.050
Tempo-0.0700.1440.0000.1170.070-0.136-0.0220.0070.0721.000-0.0220.0430.0410.0420.0290.0470.0270.045
Duration_ms-0.1410.018-0.005-0.044-0.161-0.0610.062-0.020-0.094-0.0221.0000.1750.1250.1680.0870.0830.0190.022
Views0.1330.1390.0130.2510.026-0.119-0.182-0.0120.0800.0430.1751.0000.9620.9120.6080.0150.0800.069
Likes0.1560.1280.0160.2570.086-0.127-0.183-0.0170.0380.0410.1250.9621.0000.9480.6110.0070.0820.071
Comments0.1150.1530.0120.2540.065-0.166-0.163-0.0070.0250.0420.1680.9120.9481.0000.5680.0000.0150.009
Spotify_stream0.0520.045-0.0070.141-0.018-0.115-0.113-0.032-0.0060.0290.0870.6080.6110.5681.0000.0500.0890.093
Album_type0.1160.0750.0430.1090.0700.0510.0330.0290.0470.0470.0830.0150.0070.0000.0501.0000.0440.108
Licensed0.0190.0850.0000.1100.0640.0710.0580.0130.0390.0270.0190.0800.0820.0150.0890.0441.0000.817
Official_video0.0520.1150.0080.1540.0680.0910.0660.0080.0500.0450.0220.0690.0710.0090.0930.1080.8171.000

Missing values

2023-07-16T17:22:11.045568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-16T17:22:11.697534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-16T17:22:12.438519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

ArtistTrackAlbumAlbum_typeDanceabilityEnergyKeyLoudnessSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoDuration_msViewsLikesCommentsLicensedOfficial_videoSpotify_stream
0GorillazFeel Good Inc.Demon Daysalbum0.8180.7056.0-6.6790.17700.0083600.0023300.61300.772138.559222640.0693555221.06220896.0169907.0TrueTrue1.040235e+09
1GorillazRhinestone EyesPlastic Beachalbum0.6760.7038.0-5.8150.03020.0869000.0006870.04630.85292.761200173.072011645.01079128.031003.0TrueTrue3.100837e+08
2GorillazNew Gold (feat. Tame Impala and Bootie Brown)New Gold (feat. Tame Impala and Bootie Brown)single0.6950.9231.0-3.9300.05220.0425000.0469000.11600.551108.014215150.08435055.0282142.07399.0TrueTrue6.306347e+07
3GorillazOn Melancholy HillPlastic Beachalbum0.6890.7392.0-5.8100.02600.0000150.5090000.06400.578120.423233867.0211754952.01788577.055229.0TrueTrue4.346636e+08
4GorillazClint EastwoodGorillazalbum0.6630.69410.0-8.6270.17100.0253000.0000000.06980.525167.953340920.0618480958.06197318.0155930.0TrueTrue6.172597e+08
5GorillazDAREDemon Daysalbum0.7600.89111.0-5.8520.03720.0229000.0869000.29800.966120.264245000.0259021161.01844658.072008.0TrueTrue3.238503e+08
6GorillazNew Gold (feat. Tame Impala and Bootie Brown) - Dom Dolla RemixNew Gold (feat. Tame Impala and Bootie Brown) [Dom Dolla Remix]single0.7160.8974.0-7.1850.06290.0120000.2620000.32500.358127.030274142.0451996.011686.0241.0FalseTrue1.066615e+07
7GorillazShe's My Collar (feat. Kali Uchis)Humanz (Deluxe)album0.7260.81511.0-5.8860.03130.0079900.0810000.11200.462140.158209560.01010982.017675.0260.0FalseFalse1.596059e+08
8GorillazCracker Island (feat. Thundercat)Cracker Island (feat. Thundercat)single0.7410.9132.0-3.3400.04650.0034300.1030000.32500.643120.012213750.024459820.0739527.020296.0TrueTrue4.267190e+07
9GorillazDirty HarryDemon Daysalbum0.6250.87710.0-7.1760.16200.0315000.0811000.67200.865192.296230426.0154761056.01386920.039240.0TrueTrue1.910747e+08
ArtistTrackAlbumAlbum_typeDanceabilityEnergyKeyLoudnessSpeechinessAcousticnessInstrumentalnessLivenessValenceTempoDuration_msViewsLikesCommentsLicensedOfficial_videoSpotify_stream
20708SICK LEGENDPART OF ME HARDSTYLE (SPED UP)PART OF ME HARDSTYLE (SPED UP)single0.6420.94910.0-3.0550.03730.0194000.2270000.41400.6920101.959112971.040814.0640.00.0TrueTrue17721588.0
20709SICK LEGENDSUMMER TIME SADNESS HARDSTYLESUMMER TIME SADNESS HARDSTYLEsingle0.4900.8241.0-6.3260.15800.0888000.0000150.36300.3200166.837104910.023719.0362.00.0TrueTrue10838254.0
20710SICK LEGENDPART OF ME HARDSTYLEPART OF ME HARDSTYLEsingle0.5190.9027.0-3.4940.04200.0120000.0001320.26600.6570174.790131657.0370711.04639.00.0TrueTrue16332133.0
20711SICK LEGENDMIDDLE OF THE NIGHT - HARDSTYLE REMIXMIDDLE OF THE NIGHT - HARDSTYLE REMIXsingle0.2920.6922.0-7.1980.03760.0001180.0003540.38200.0544185.467175147.0254268.03472.00.0TrueTrue17125177.0
20712SICK LEGENDEVERYTIME WE TOUCH HARDSTYLE (SPED UP)EVERYTIME WE TOUCH HARDSTYLE (SPED UP)single0.5540.8741.0-5.1990.04800.2350000.0000000.31800.6170102.16794000.016004.0267.00.0TrueTrue9921887.0
20713SICK LEGENDJUST DANCE HARDSTYLEJUST DANCE HARDSTYLEsingle0.5820.9265.0-6.3440.03280.4480000.0000000.08390.658090.00294667.071678.01113.00.0TrueTrue9227144.0
20714SICK LEGENDSET FIRE TO THE RAIN HARDSTYLESET FIRE TO THE RAIN HARDSTYLEsingle0.5310.9364.0-1.7860.13700.0280000.0000000.09230.6570174.869150857.0164741.02019.00.0TrueTrue10898176.0
20715SICK LEGENDOUTSIDE HARDSTYLE SPED UPOUTSIDE HARDSTYLE SPED UPsingle0.4430.8304.0-4.6790.06470.0243000.0000000.15400.4190168.388136842.035646.0329.00.0TrueTrue6226110.0
20716SICK LEGENDONLY GIRL HARDSTYLEONLY GIRL HARDSTYLEsingle0.4170.7679.0-4.0040.41900.3560000.0184000.10800.5390155.378108387.06533.088.00.0TrueTrue6873961.0
20717SICK LEGENDMISS YOU HARDSTYLEMISS YOU HARDSTYLEsingle0.4980.9386.0-4.5430.10700.0027700.9110000.13600.0787160.067181500.0158697.02484.00.0TrueTrue5695584.0